Flat-panel imagers (FPIs) are being investigated in a host of advanced x-ray imaging modalities that offer improved tissue visualization and depth discrimination, including dual-energy (DE) imaging, tomosynthesis, and cone-beam CT (CBCT). Each represents a promising technology for diagnostic and image-guided procedures. In DE imaging, two images acquired at different x-ray energies are processed to yield images of bone or soft-tissue. In tomosynthesis and CBCT, the x-ray source and FPI move about the patient, and 3D images are reconstructed from multiple perspectives. Realizing the full potential of these modalities requires quantitative evaluation of imaging performance and a methodology for revealing the physical factors that limit image quality. Conventional Fourier-based metrics, such as Noise-Equivalent Quanta (NEQ), provide practical, prevalent figures of merit for spatial resolution and signal-to-noise ratio. For these advanced imaging modalities, however, there is currently no rigorous performance metrology (Fourier-based or otherwise);furthermore, the NEQ conventionally describes only the performance of the detector, and considers neither the structures of interest in the image (i.e., the task) nor the response of observers. This proposal pursues a fundamental image science approach to performance evaluation in these advanced modalities, breaking new ground in numerous respects: 1.) The NEQ and associated Fourier metrics are extended to each of the advanced modalities to provide an experimental and theoretical methodology for imaging performance evaluation;2.) Structures of interest in the image are quantified in terms of the imaging t ask, considering a variety of simple and higher-order tasks (detection, localization, and size estimation) in relation to two of the most lethal cancers (lung carcinoma and liver metastases);and 3.) Quantitative formulations of imaging task and NEQ are rigorously combined to yield task-based metrics for imaging performance in DE imaging, tomosynthesis, and CBCT, and the extent to which such task-based metrics provide a meaningful surrogate for image quality is validated by correlation with the response of human observers. Hence, this proposal begins to bridge the gap between the prevalent Fourier-based approach and traditional observer-based approaches (e.g., ROC analysis) through rigorous quantitation of imaging task. For example, imaging performance in early detection of lung nodules is evaluated using Detection and Size Estimation tasks for DE imaging and tomosynthesis, while guidance of RF ablation or radiation therapy of liver metastases is evaluated in terms of a Localization task for CBCT. Successful completion of this program will offer a practical, task-driven approach to the design, evaluation, and optimization of these and other novel imaging modalities.